Visualisation_Pro
IsaevaA.S.
2024-11-17
Чтение данных
- Загрузите датасет very_low_birthweight.RDS (лежит в папке домашнего задания). Переменными исхода являются колонки ‘dead’, а также время от рождения до смерти или выписки (выводятся из ‘birth’ и ‘exit’. 7 пациентов были выписаны до рождения). Сделайте копию датасета, в которой удалите колонки с количеством пропусков больше 100, а затем удалите все строки с пропусками.
original_data<-readRDS("C:/Users/User/Downloads/very_low_birthweight.RDS")
original_data## birth exit hospstay lowph pltct race bwt gest
## 1 81.511 81.604 34 NA 100 white 1250 35.0
## 2 81.514 81.539 9 7.250000 244 white 1370 32.0
## 3 81.552 81.552 -2 7.059998 114 black 620 23.0
## 4 81.558 81.667 40 7.250000 182 black 1480 32.0
## 5 81.593 81.599 2 6.969997 54 black 925 28.0
## 6 81.602 81.771 62 7.189999 NA white 940 28.0
## 7 81.610 81.697 32 7.320000 282 black 1255 29.5
## 8 NA NA NA NA NA <NA> 600 26.0
## 9 NA NA NA NA NA <NA> 700 24.0
## 10 81.624 81.700 28 7.160000 153 black 1350 34.0
## 11 81.626 81.730 38 7.039997 229 white 1310 32.0
## 12 NA NA NA NA NA <NA> 550 24.0
## 13 81.684 81.854 62 7.179996 182 black 1110 28.0
## 14 81.689 81.878 69 7.419998 361 white 1180 28.0
## 15 81.695 81.697 1 7.119999 378 white 970 28.0
## 16 81.697 81.952 93 7.239998 255 black 770 26.0
## 17 81.706 81.826 44 7.129997 186 white 1490 33.0
## 18 81.711 81.848 50 7.269997 NA black 1170 31.0
## 19 81.711 81.892 66 7.179996 260 black 1360 31.0
## 20 81.719 81.897 65 7.070000 183 white 1330 31.0
## 21 81.747 81.867 44 7.289997 134 white 1000 28.0
## 22 81.758 81.949 70 7.129997 229 black 1120 29.0
## 23 81.763 81.996 85 7.189999 68 white 740 26.0
## 24 NA NA NA NA NA <NA> NA NA
## 25 81.777 81.936 58 7.369999 174 black 1100 29.0
## 26 NA NA NA NA NA <NA> NA 26.0
## 27 81.826 81.826 -2 6.939999 261 black 820 28.0
## 28 81.834 81.046 -288 7.309998 257 black 810 26.0
## 29 81.873 81.952 29 7.289997 170 white 1300 31.0
## 30 81.963 82.152 69 7.299999 218 black 1110 30.0
## 31 81.966 82.171 75 7.250000 179 black 970 29.0
## 32 81.966 81.169 -291 7.199997 115 black 760 29.0
## 33 NA NA NA NA NA <NA> 560 24.0
## 34 NA NA NA NA NA <NA> 540 24.0
## 35 81.979 82.075 35 7.339996 270 black 1440 30.0
## 36 81.988 82.081 34 7.230000 240 black 1360 29.0
## 37 NA NA NA NA NA <NA> 750 24.0
## 38 NA NA NA NA NA <NA> 880 26.0
## 39 82.026 82.259 85 NA NA white 990 27.0
## 40 82.026 82.259 85 7.299999 350 white 840 27.0
## 41 82.026 82.152 46 7.320000 250 black 1420 30.0
## 42 82.053 82.513 168 7.160000 74 white 1250 32.0
## 43 82.056 82.146 33 6.899998 181 white 1360 30.0
## 44 NA NA NA NA NA <NA> 590 23.0
## 45 82.084 82.198 42 7.289997 234 black 1030 29.0
## 46 82.108 82.242 49 7.259998 174 black 1070 28.0
## 47 82.108 82.201 34 7.289997 51 black 1500 31.0
## 48 82.133 82.242 40 7.059998 200 white 1500 28.5
## 49 NA NA NA NA NA <NA> 1300 30.0
## 50 82.163 82.333 62 7.179996 197 white 1100 30.0
## 51 82.163 82.294 48 7.179996 270 black 1400 30.0
## 52 82.168 82.168 -2 6.829998 NA black 740 NA
## 53 82.204 82.382 65 7.129997 197 white 1230 28.0
## 54 82.207 82.513 112 6.959999 132 white 940 28.0
## 55 82.209 82.472 96 7.199997 247 white 920 26.0
## 56 82.240 82.453 78 7.160000 189 black 1420 29.0
## 57 82.248 82.248 -2 7.109997 274 black 1030 27.0
## 58 82.267 82.426 58 6.969997 227 white 1360 28.0
## 59 82.270 82.338 25 7.199997 226 black 1180 29.0
## 60 82.270 82.385 42 7.219997 144 black 1240 30.0
## 61 82.297 82.297 -2 7.250000 NA black 930 25.0
## 62 82.300 82.396 35 7.389999 191 black 1320 31.0
## 63 NA NA NA NA NA <NA> 550 23.0
## 64 NA NA NA NA NA <NA> 540 23.0
## 65 82.300 82.338 14 7.259998 256 black 990 27.5
## 66 82.300 82.467 61 7.219997 267 black 990 27.5
## 67 82.300 82.303 1 6.849998 245 black 800 28.0
## 68 82.330 82.445 42 7.019997 216 white 1270 29.0
## 69 82.349 82.407 21 7.169998 247 white 1250 29.0
## 70 82.349 82.746 145 7.259998 191 black 1050 27.0
## 71 NA NA NA NA NA <NA> 580 23.0
## 72 82.357 82.475 43 7.279999 209 white 1420 33.0
## 73 NA NA NA NA NA <NA> 630 23.0
## 74 82.366 82.475 40 7.079998 571 black 1450 30.0
## 75 82.371 82.470 36 7.279999 319 white 1270 29.0
## 76 82.390 82.552 59 7.230000 259 white 1090 29.0
## 77 82.418 82.593 64 7.219997 168 native American 830 28.0
## 78 82.420 82.563 52 7.299999 76 black 830 28.0
## 79 82.420 82.491 26 7.149998 NA white 1380 32.0
## 80 82.434 82.513 29 7.230000 211 black 1330 32.0
## 81 82.437 82.511 27 7.349998 237 white 1440 28.0
## 82 82.445 82.590 53 7.209999 397 oriental 960 28.0
## 83 82.459 82.513 20 7.339996 220 black 1240 31.5
## 84 82.513 82.853 124 7.299999 227 white 900 27.0
## 85 82.511 82.552 15 7.199997 132 black 1230 30.0
## 86 82.524 82.571 17 7.019997 135 white 1360 33.0
## 87 82.535 82.612 28 7.000000 196 black 1170 29.0
## 88 82.535 82.804 98 7.169998 107 white 790 27.0
## 89 NA NA NA NA NA <NA> 805 25.0
## 90 82.563 82.565 1 7.000000 NA black 675 25.0
## 91 82.571 82.606 13 7.320000 232 black 1140 32.0
## 92 82.579 82.642 23 7.199997 209 white 1250 29.0
## 93 82.590 82.669 29 7.239998 NA black 670 26.0
## 94 82.585 82.664 29 7.009998 24 white 1000 32.0
## 95 82.598 82.850 92 7.129997 109 black 1325 30.0
## 96 82.598 82.773 64 7.160000 NA black 1050 30.0
## 97 82.601 82.836 86 7.129997 187 white 1310 30.0
## 98 82.601 82.836 86 7.189999 161 white 1450 30.0
## 99 82.615 82.697 30 7.299999 142 black 1200 28.0
## 100 82.631 82.669 14 7.459999 NA white 1210 33.0
## 101 82.637 82.894 94 7.139999 286 black 880 27.0
## 102 82.672 82.787 42 7.239998 183 black 1240 28.0
## 103 82.675 82.984 113 6.529999 144 black 850 26.0
## 104 82.689 82.721 12 7.259998 237 black 1460 32.0
## 105 82.689 82.716 10 7.250000 288 black 1475 32.0
## 106 NA NA NA NA NA <NA> 650 25.0
## 107 82.710 82.847 50 7.329998 294 white 1180 29.0
## 108 82.713 82.842 47 7.219997 211 black 1450 30.0
## 109 82.716 82.842 46 7.219997 190 black 1390 32.0
## 110 82.738 83.140 147 7.209999 NA white 875 30.0
## 111 82.795 83.190 144 7.199997 248 black 1120 29.0
## 112 82.817 82.820 1 6.809998 NA white 600 24.0
## 113 NA NA NA NA NA <NA> 1040 25.0
## 114 82.834 82.856 8 7.219997 256 black 880 25.0
## 115 82.875 83.025 55 7.259998 334 black 1370 30.0
## 116 82.877 82.954 28 7.160000 299 white 1310 33.0
## 117 82.880 83.113 85 7.169998 130 black 865 26.5
## 118 82.883 83.151 98 7.410000 204 white 1275 28.0
## 119 82.888 82.992 38 7.199997 216 white 1160 28.0
## 120 82.888 82.976 32 7.339996 287 white 1280 28.0
## 121 82.891 83.009 43 7.339996 207 black 1100 32.0
## 122 82.891 82.921 11 7.230000 311 black 1415 31.0
## 123 NA NA NA NA NA <NA> 1100 30.0
## 124 82.894 83.009 42 7.399998 173 white 1370 30.0
## 125 82.938 83.086 54 7.019997 246 white 980 28.5
## 126 82.940 83.107 61 7.259998 216 white 1000 28.0
## 127 82.943 83.107 60 7.129997 235 oriental 1360 31.0
## 128 82.951 83.121 62 7.379997 313 black 1150 27.0
## 129 82.954 83.050 35 7.439999 260 black 1200 29.0
## 130 82.960 82.968 3 6.949997 121 white 1100 30.0
## 131 82.965 83.236 99 7.189999 181 black 730 27.5
## 132 82.973 83.198 82 7.009998 204 white 1070 29.0
## 133 82.982 83.239 94 7.160000 174 black 850 28.0
## 134 82.998 83.181 67 6.969997 223 black 1140 29.0
## 135 83.003 83.012 3 7.119999 NA black 660 25.0
## 136 83.003 83.012 3 7.349998 NA black 570 25.0
## 137 83.006 83.321 115 7.179996 180 black 1100 28.0
## 138 83.025 83.028 1 NA NA native American 1210 32.0
## 139 83.039 83.138 36 7.359997 283 black 1350 31.0
## 140 83.053 83.102 18 7.139999 149 black 940 28.0
## 141 83.066 83.611 199 7.119999 149 black 765 26.0
## 142 83.069 83.151 30 7.439999 NA black 1330 33.0
## 143 83.072 83.192 44 7.309998 183 white 1420 30.0
## 144 83.072 83.261 69 7.169998 176 white 1450 30.0
## 145 83.077 83.370 107 7.119999 117 native American 610 27.0
## 146 83.094 83.124 11 7.339996 56 white 1075 27.0
## 147 83.110 83.299 69 7.320000 219 black 1015 26.0
## 148 83.116 83.116 -2 7.230000 156 black 970 28.0
## 149 83.127 83.255 47 7.299999 157 white 1500 30.0
## 150 83.132 83.403 99 7.139999 63 black 1000 27.0
## 151 83.157 83.332 64 7.189999 148 white 870 28.0
## 152 83.165 83.305 51 7.299999 131 white 1310 31.0
## 153 83.165 83.168 1 6.779999 341 black 1130 29.0
## 154 83.173 83.313 51 7.379997 129 black 1230 31.0
## 155 83.187 83.488 110 7.019997 205 white 1390 31.0
## 156 83.195 83.329 49 7.250000 377 black 1100 29.5
## 157 83.195 83.436 88 7.219997 242 black 1150 29.5
## 158 83.239 83.348 40 7.250000 199 <NA> 1010 28.0
## 159 83.250 83.373 45 7.299999 351 black 1230 26.0
## 160 83.302 83.469 61 7.259998 226 black 1010 30.0
## 161 83.310 83.313 1 6.849998 173 white 1020 29.0
## 162 83.316 83.447 48 7.230000 186 native American 950 28.0
## 163 83.316 83.474 58 7.309998 230 black 1000 28.0
## 164 83.316 83.543 83 7.189999 239 black 1095 28.0
## 165 83.326 83.455 47 7.449997 286 black 1190 29.0
## 166 83.337 83.603 97 7.429996 416 white 1080 28.0
## 167 83.365 83.436 26 7.119999 191 white 1100 28.0
## 168 83.381 83.600 80 7.299999 246 white 1340 29.0
## 169 83.381 83.546 60 7.320000 208 white 1280 29.0
## 170 83.381 83.436 20 7.419998 289 white 1030 32.0
## 171 83.409 83.441 12 7.169998 50 native American 640 26.5
## 172 83.420 83.565 53 7.169998 252 black 880 26.5
## 173 83.422 83.469 17 7.279999 175 black 1220 28.0
## 174 83.428 83.466 14 7.339996 202 black 1080 32.0
## 175 83.431 83.507 28 7.009998 132 black 600 24.0
## 176 83.436 83.548 41 7.099998 34 native American 1110 29.0
## 177 83.466 83.589 45 7.320000 358 white 1210 30.0
## 178 83.477 83.493 6 7.139999 190 black 600 25.0
## 179 83.477 83.496 7 7.099998 28 white 1140 27.0
## 180 83.488 83.661 63 7.129997 238 native American 950 27.0
## 181 83.496 83.573 28 7.209999 224 black 790 29.0
## 182 83.515 83.554 14 7.179996 129 black 1085 27.5
## 183 83.515 83.890 137 7.149998 106 black 780 27.5
## 184 83.515 83.603 32 7.389999 137 black 1180 28.0
## 185 83.524 83.644 44 7.359997 227 white 1180 28.0
## 186 83.537 83.619 30 7.079998 177 black 1240 29.0
## 187 83.543 83.661 43 7.369999 90 black 1100 32.0
## 188 83.546 83.661 42 7.329998 271 black 1110 29.5
## 189 83.559 83.871 114 7.259998 179 black 670 26.5
## 190 83.559 83.636 28 7.320000 193 black 1430 32.0
## 191 83.573 83.699 46 7.169998 212 black 1077 30.0
## 192 83.573 83.589 6 7.169998 247 white 808 27.5
## 193 83.578 83.628 18 7.189999 135 black 1340 29.0
## 194 83.592 83.592 -2 6.919998 100 white 880 28.0
## 195 83.589 83.595 2 7.000000 187 white 880 28.0
## 196 83.595 83.652 21 7.369999 175 white 1230 29.0
## 197 83.600 83.682 30 7.179996 122 black 1350 30.0
## 198 83.603 83.786 67 7.089996 272 white 1290 32.0
## 199 83.614 83.836 81 7.209999 267 black 1100 28.0
## 200 83.617 83.671 20 7.250000 214 black 670 25.5
## 201 83.625 83.644 7 7.369999 246 black 1360 31.5
## 202 83.639 84.110 172 7.139999 268 black 1450 32.0
## 203 83.655 83.929 100 7.139999 227 black 820 28.0
## 204 83.655 83.655 -2 7.199997 207 black 670 22.0
## 205 83.661 83.737 28 7.239998 258 black 1280 30.0
## 206 83.666 83.877 77 6.989998 110 white 975 27.5
## 207 83.674 83.797 45 7.119999 57 white 1275 28.0
## 208 83.674 83.775 37 7.299999 370 white 1120 28.0
## 209 83.723 83.726 1 6.919998 223 black 600 23.0
## 210 83.680 83.699 7 7.410000 187 white 1230 32.0
## 211 83.680 83.907 83 7.079998 261 white 1060 29.0
## 212 83.691 83.710 7 7.339996 309 black 1290 30.0
## 213 83.693 83.762 25 7.379997 130 black 825 31.0
## 214 83.715 83.721 2 7.189999 NA black 652 25.0
## 215 83.732 83.732 -2 7.109997 192 white 1100 27.0
## 216 83.754 83.814 22 7.339996 253 white 1150 29.0
## 217 83.754 83.921 61 7.339996 88 black 870 36.0
## 218 83.762 84.257 181 7.160000 141 white 890 27.0
## 219 83.767 83.775 3 7.329998 234 black 1430 31.0
## 220 83.775 84.986 442 7.079998 188 black 1140 29.0
## 221 83.775 83.118 -240 7.059998 56 black 1140 29.0
## 222 83.775 83.828 19 7.219997 187 black 1470 34.0
## 223 83.786 83.888 37 7.169998 201 black 1180 29.0
## 224 83.792 83.860 25 7.089996 49 black 765 26.0
## 225 83.808 83.871 23 7.129997 226 black 1390 29.0
## 226 83.814 84.099 104 7.289997 168 white 900 30.0
## 227 83.830 83.904 27 7.339996 134 black 980 32.0
## 228 83.860 84.019 58 7.070000 129 native American 1180 30.0
## 229 83.871 83.967 35 7.129997 77 native American 1100 32.0
## 230 83.882 83.970 32 7.320000 236 white 1450 31.0
## 231 83.882 83.888 2 7.279999 201 white 1480 31.0
## 232 83.896 84.033 50 7.309998 306 white 1270 31.5
## 233 83.896 84.005 40 7.119999 155 white 1490 31.5
## 234 83.901 84.657 276 7.369999 301 black 820 28.0
## 235 83.907 83.929 8 7.160000 207 white 1240 29.0
## 236 83.907 83.953 17 6.980000 154 white 1060 31.5
## 237 83.932 84.066 49 6.959999 70 black 1130 29.0
## 238 83.940 84.142 74 7.209999 224 white 800 28.0
## 239 83.967 84.208 88 6.919998 126 black 880 26.0
## 240 83.992 84.216 82 7.099998 175 black 720 27.0
## 241 84.000 84.208 76 7.250000 243 white 980 29.0
## 242 84.000 84.183 67 7.299999 240 white 1150 29.0
## 243 84.005 84.044 14 7.289997 267 black 1320 31.0
## 244 84.011 84.255 89 7.339996 84 white 990 29.5
## 245 84.027 84.364 123 7.039997 168 black 587 25.0
## 246 84.041 84.101 22 7.259998 418 white 1380 29.5
## 247 84.049 84.055 2 7.029999 323 white 700 25.0
## 248 84.071 84.233 59 7.139999 106 white 1080 28.0
## 249 84.085 84.290 75 7.179996 129 black 900 27.0
## 250 84.118 84.145 10 7.379997 313 black 1300 30.0
## 251 84.123 84.257 49 7.379997 289 black 980 27.5
## 252 NA NA NA 7.230000 205 black 1290 33.5
## 253 84.142 84.271 47 7.219997 214 black 1375 33.0
## 254 84.153 84.671 189 NA 103 white 880 29.0
## 255 84.186 84.370 67 7.239998 234 white 1305 29.0
## 256 84.189 84.252 23 7.349998 379 black 1410 32.0
## 257 84.197 84.424 83 6.889999 126 white 1500 29.0
## 258 84.200 84.205 2 6.759998 249 black 610 26.0
## 259 84.203 84.219 6 7.349998 252 white 1490 30.0
## 260 84.211 84.225 5 7.299999 212 black 1460 30.0
## 261 84.205 84.318 41 7.160000 84 black 850 26.0
## 262 84.219 84.257 14 7.209999 190 black 1450 30.0
## 263 84.249 84.460 77 7.179996 282 black 1120 31.0
## 264 84.257 84.345 32 7.480000 356 black 1290 30.0
## 265 84.274 84.318 16 7.359997 172 black 1375 32.0
## 266 84.282 84.298 6 7.189999 223 white 790 26.0
## 267 84.287 84.361 27 7.369999 384 white 1350 32.0
## 268 84.298 84.471 63 7.089996 235 white 1200 31.0
## 269 84.298 84.444 53 7.059998 256 white 1350 28.0
## 270 84.301 84.501 73 7.059998 82 black 740 32.0
## 271 84.318 84.386 25 7.349998 202 white 1180 31.0
## 272 84.329 84.638 113 7.129997 258 white 1090 29.0
## 273 84.337 84.471 49 7.239998 185 black 1160 28.5
## 274 84.337 84.449 41 7.239998 138 black 1280 28.5
## 275 84.348 84.424 28 7.209999 185 black 1420 33.5
## 276 84.350 84.564 78 7.169998 135 white 905 27.0
## 277 84.378 84.597 80 7.000000 148 black 860 26.5
## 278 84.389 84.482 34 7.320000 269 black 1250 30.0
## 279 84.411 84.594 67 7.230000 253 black 760 25.0
## 280 84.441 84.520 29 7.349998 168 white 1160 34.0
## 281 84.463 84.531 25 7.119999 158 white 1330 29.0
## 282 84.463 84.531 25 7.250000 251 white 1240 29.0
## 283 84.474 84.476 1 6.699997 NA black 640 24.0
## 284 84.476 84.520 16 7.199997 269 black 1330 32.0
## 285 84.490 86.672 797 7.250000 251 white 1240 30.0
## 286 84.496 84.561 24 7.369999 365 black 1500 34.0
## 287 84.501 84.507 2 7.009998 183 black 990 26.0
## 288 84.504 84.591 32 7.199997 250 black 1410 32.0
## 289 84.509 84.526 6 7.359997 208 black 1335 30.0
## 290 84.517 84.567 18 6.889999 91 white 1115 28.0
## 291 84.534 84.542 3 NA 306 white 980 27.0
## 292 84.539 84.578 14 7.259998 233 white 1240 31.0
## 293 84.542 84.698 57 6.980000 244 black 1200 29.0
## 294 84.545 NA NA NA NA black 1500 40.0
## 295 84.548 84.597 18 7.329998 216 black 1110 33.0
## 296 84.559 84.931 136 7.079998 142 black 950 26.0
## 297 84.561 84.756 71 7.299999 190 black 1000 26.0
## 298 84.569 84.652 30 7.179996 260 black 1000 28.0
## 299 84.572 84.676 38 7.339996 179 white 1320 30.0
## 300 84.572 84.635 23 7.389999 160 white 1480 32.0
## 301 84.575 84.638 23 7.109997 116 white 970 27.0
## 302 84.580 84.619 14 7.179996 302 black 1420 29.0
## 303 84.597 84.635 14 7.379997 273 black 1480 32.0
## 304 84.608 84.720 41 7.000000 254 white 900 26.0
## 305 84.621 84.676 20 6.859997 131 black 625 24.0
## 306 84.621 84.676 20 7.209999 188 white 1480 32.0
## 307 84.630 84.695 24 7.129997 222 white 1420 31.0
## 308 84.638 84.674 13 7.079998 178 black 780 26.0
## 309 84.638 84.715 28 7.379997 319 black 1160 28.0
## 310 84.641 84.704 23 7.160000 302 black 1000 29.0
## 311 84.643 84.786 52 NA 220 black 1440 32.0
## 312 84.668 84.668 -2 NA 272 black 745 25.0
## 313 84.676 84.682 2 7.029999 107 <NA> 1025 29.0
## 314 84.679 84.830 55 7.070000 234 white 880 27.0
## 315 84.682 84.838 57 7.179996 157 white 1200 31.0
## 316 84.684 84.742 21 7.329998 302 black 1390 31.0
## 317 84.687 NA NA 7.179996 181 black 1220 31.0
## 318 84.693 84.824 48 7.230000 199 white 1470 31.0
## 319 84.706 84.736 11 7.320000 207 black 1380 33.0
## 320 84.706 84.739 12 7.489998 278 black 1500 34.0
## 321 84.715 84.808 34 7.329998 365 black 1110 29.0
## 322 84.723 84.827 38 7.309998 150 white 920 29.0
## 323 84.720 85.114 144 7.189999 134 black 1020 28.0
## 324 84.736 84.769 12 7.149998 204 black 1250 29.0
## 325 84.739 84.758 7 7.309998 284 black 1440 32.0
## 326 84.747 84.862 42 7.169998 257 black 1200 28.0
## 327 84.747 NA NA NA 120 white 1580 31.0
## 328 84.758 84.821 23 7.289997 329 black 920 29.0
## 329 84.769 84.849 29 7.230000 257 black 1320 31.0
## 330 84.772 84.832 22 7.230000 242 black 1200 29.0
## 331 84.775 84.909 49 7.119999 155 black 850 27.0
## 332 84.780 84.958 65 7.269997 145 black 1000 28.0
## 333 84.794 84.928 49 7.070000 240 white 1120 30.0
## 334 84.802 84.942 51 7.209999 106 black 980 33.0
## 335 84.824 84.841 6 6.969997 152 white 1010 28.0
## 336 84.827 84.854 10 7.339996 206 white 1480 32.0
## 337 84.830 84.871 15 7.129997 227 black 1280 30.0
## 338 84.841 84.966 46 7.179996 86 black 980 28.0
## 339 84.860 84.862 1 6.699997 NA white 800 27.0
## 340 84.871 84.950 29 7.259998 82 white 1260 35.0
## 341 84.879 84.901 8 7.250000 67 black 1300 29.0
## 342 84.884 85.128 89 6.929996 125 black 820 27.0
## 343 84.887 85.125 87 7.209999 212 white 770 27.0
## 344 84.893 84.906 5 7.359997 308 black 1300 29.0
## 345 84.903 84.988 31 7.359997 238 black 1480 31.0
## 346 84.903 84.923 7 7.199997 259 black 1480 32.0
## 347 84.906 84.939 12 7.389999 122 black 1260 35.0
## 348 84.906 85.013 39 7.119999 207 black 1280 29.0
## 349 84.906 84.912 2 7.199997 196 black 400 24.0
## 350 84.909 85.038 47 7.269997 263 white 760 25.0
## 351 84.909 84.945 13 7.269997 173 <NA> 1380 29.0
## 352 84.920 85.314 144 7.149998 100 black 620 27.0
## 353 84.928 84.958 11 7.239998 286 black 1030 28.0
## 354 84.931 85.035 38 7.129997 336 black 760 26.0
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## 522 born at Duke 1 0 1 1 0 abdominal 3 0 0 0 0
## 523 born at Duke 1 0 1 1 0 abdominal 2 0 0 0 0
## 524 transported 0 8 0 NA NA vaginal 2 1 0 1 1
## 525 born at Duke 0 3 0 0 1 vaginal 6 1 0 1 1
## 526 transported 0 NA 0 NA NA abdominal 9 1 1 0 0
## 527 born at Duke 0 NA 0 0 0 vaginal 5 0 0 0 0
## 528 born at Duke 0 3 0 1 0 vaginal 2 1 0 1 1
## 529 born at Duke 1 10 0 1 0 vaginal 7 0 0 0 0
## 530 born at Duke 1 10 0 1 0 vaginal 8 0 0 0 0
## 531 born at Duke 0 7 0 0 0 vaginal 5 0 0 0 0
## 532 born at Duke 0 4 0 1 0 abdominal 8 0 0 0 0
## 533 born at Duke 0 28 0 0 1 abdominal 3 0 0 1 0
## 534 born at Duke 1 0 0 1 1 abdominal 8 0 0 1 0
## 535 born at Duke 1 0 0 1 1 abdominal 8 0 0 0 0
## 536 born at Duke 1 0 0 1 1 abdominal 8 1 0 0 0
## 537 born at Duke 1 0 0 1 1 abdominal 8 1 0 0 0
## 538 born at Duke 0 3 0 1 0 abdominal 2 1 0 0 0
## 539 born at Duke 0 0 0 1 0 abdominal 8 0 0 0 0
## 540 born at Duke 0 4 0 0 0 abdominal 9 0 0 0 0
## 541 born at Duke 0 72 0 0 0 abdominal 1 1 0 1 1
## 542 transported 0 8 0 NA NA vaginal 7 1 0 0 0
## 543 born at Duke 0 0 0 1 0 abdominal 1 1 0 0 1
## 544 born at Duke 0 NA 0 1 0 vaginal 6 1 0 0 NA
## 545 born at Duke 0 0 0 0 0 abdominal 8 0 0 0 0
## 546 born at Duke 0 2 0 1 1 vaginal 7 0 0 0 0
## 547 born at Duke 0 9 0 1 0 abdominal 4 1 1 0 0
## 548 born at Duke 0 0 1 0 0 abdominal 3 1 0 0 1
## 549 born at Duke 0 20 0 1 1 vaginal 8 0 0 0 0
## 550 born at Duke 1 2 0 1 0 vaginal 5 0 0 0 0
## 551 born at Duke 1 2 0 1 0 vaginal 7 0 0 0 0
## 552 born at Duke 0 2 0 1 0 vaginal 2 0 0 0 0
## 553 born at Duke 0 10 0 0 0 vaginal 1 1 0 0 NA
## 554 transported 0 NA 0 NA NA abdominal 3 1 0 1 1
## 555 born at Duke 0 7 0 0 0 vaginal 4 1 0 1 1
## 556 born at Duke 0 NA 0 1 1 vaginal 7 1 0 0 0
## 557 born at Duke 1 NA NA 1 0 abdominal 3 0 0 0 0
## 558 born at Duke 0 13 0 0 0 vaginal 4 1 0 0 0
## 559 transported 0 NA 0 1 1 vaginal 1 1 0 0 0
## 560 born at Duke 0 8 0 0 0 vaginal 9 1 0 0 0
## 561 born at Duke 0 0 1 1 0 abdominal 3 0 0 0 0
## 562 born at Duke 0 0 0 1 0 abdominal 7 0 0 0 0
## 563 born at Duke 0 0 0 1 1 abdominal 4 0 0 0 0
## 564 transported 0 4 0 NA NA vaginal 1 1 0 0 0
## 565 transported 0 NA 0 NA NA vaginal 5 1 0 1 1
## 566 born at Duke 0 4 0 1 0 abdominal 4 1 1 1 0
## 567 born at Duke 0 NA 0 0 0 vaginal 2 1 1 0 NA
## 568 born at Duke 0 3 0 0 0 vaginal 1 1 0 1 1
## 569 born at Duke 1 0 1 1 0 abdominal 6 1 0 1 1
## 570 born at Duke 1 0 1 1 0 abdominal 6 1 1 1 NA
## 571 transported 1 23 0 NA NA vaginal 6 0 0 0 0
## 572 transported 1 23 0 NA NA vaginal 3 1 0 1 0
## 573 born at Duke 0 NA 0 NA NA vaginal 5 0 0 0 0
## 574 transported 0 10 0 NA NA vaginal 1 1 1 1 1
## 575 born at Duke 0 0 0 0 0 abdominal 9 0 0 0 0
## 576 born at Duke 0 0 0 0 0 abdominal 1 1 0 NA 1
## 577 transported 1 11 0 NA NA vaginal NA 0 0 0 0
## 578 born at Duke 0 6 0 0 0 vaginal 3 0 0 0 0
## 579 born at Duke 1 7 NA 0 0 abdominal 6 1 0 1 1
## 580 born at Duke 1 7 NA 0 0 abdominal 6 1 1 1 1
## 581 born at Duke 0 0 0 0 1 abdominal 5 1 0 1 0
## 582 transported 0 NA 0 NA NA abdominal 2 1 0 0 NA
## 583 born at Duke 0 26 0 0 0 vaginal 2 1 1 0 1
## 584 born at Duke 0 4 0 0 0 vaginal 6 0 0 0 0
## 585 born at Duke 0 NA 0 1 1 vaginal 7 0 0 0 0
## 586 born at Duke 0 0 0 1 0 abdominal 8 0 0 0 0
## 587 born at Duke 0 NA 0 0 1 vaginal 7 1 0 0 0
## 588 born at Duke 0 8 0 1 1 vaginal 3 0 0 0 1
## 589 transported 0 NA 0 NA NA abdominal 1 0 0 0 0
## 590 born at Duke 0 NA 0 1 1 vaginal 6 0 0 0 0
## 591 born at Duke 0 NA 0 0 0 vaginal 7 0 0 0 0
## 592 born at Duke 1 0 0 1 1 abdominal 5 0 0 0 0
## 593 born at Duke 0 9 0 1 1 vaginal 6 0 0 1 0
## 594 born at Duke 0 0 1 0 0 abdominal 2 1 0 0 0
## 595 transported 0 NA 0 0 0 vaginal 8 0 0 0 0
## 596 born at Duke 0 25 0 0 1 vaginal 6 1 1 0 NA
## 597 transported 0 27 0 0 1 vaginal 8 1 0 0 0
## 598 born at Duke 0 8 0 0 0 vaginal 3 1 0 1 NA
## 599 transported 0 15 0 NA NA vaginal 3 0 0 0 0
## 600 transported 1 NA 0 0 1 abdominal 3 1 1 1 1
## 601 transported 1 NA 0 0 1 abdominal 3 1 0 1 1
## 602 born at Duke 0 NA 0 NA NA vaginal 6 0 0 0 0
## 603 transported 0 4 0 NA NA abdominal 0 0 0 0 0
## 604 born at Duke 0 11 0 0 0 vaginal 5 1 0 0 0
## 605 born at Duke 0 0 0 1 0 abdominal 7 0 0 0 0
## 606 born at Duke 0 7 0 0 0 vaginal 7 1 1 0 0
## 607 born at Duke 0 3 0 0 0 vaginal 3 NA 0 0 NA
## 608 born at Duke 0 10 0 1 1 abdominal 9 0 0 0 0
## 609 born at Duke 1 0 0 1 0 abdominal 7 0 0 0 0
## 610 born at Duke 1 0 0 1 0 abdominal 6 0 0 0 0
## 611 born at Duke 0 0 0 0 0 abdominal 7 1 1 0 1
## 612 transported 0 2 0 NA NA abdominal 4 1 1 0 NA
## 613 born at Duke 0 NA 0 0 0 vaginal 3 0 0 0 0
## 614 born at Duke 0 7 0 0 0 abdominal 4 NA 1 0 NA
## 615 born at Duke 0 17 0 0 0 vaginal 4 1 0 0 1
## 616 transported 0 NA 0 NA NA vaginal 7 1 1 1 0
## 617 transported 0 NA NA NA NA abdominal 1 1 0 0 0
## 618 <NA> 0 NA 0 NA NA vaginal 2 NA NA NA 1
## 619 born at Duke 0 4 0 0 1 vaginal 2 1 0 0 1
## 620 born at Duke 0 0 0 1 0 abdominal 0 1 1 0 1
## 621 born at Duke 1 0 NA NA NA abdominal 6 1 1 NA 1
## 622 born at Duke 1 0 0 1 1 abdominal 8 0 0 0 0
## 623 born at Duke 0 6 0 0 0 abdominal 6 1 0 1 0
## 624 born at Duke 1 0 0 1 1 abdominal 8 1 1 1 0
## 625 born at Duke 1 0 0 1 1 abdominal 8 1 1 1 0
## 626 born at Duke 1 0 0 1 1 abdominal 7 1 0 1 0
## 627 born at Duke 0 2 NA 0 0 vaginal 6 1 1 0 NA
## 628 born at Duke 1 5 0 0 0 abdominal 1 0 0 0 0
## 629 born at Duke 1 5 0 0 0 abdominal 1 1 0 1 0
## 630 born at Duke 0 0 0 0 0 abdominal 3 1 1 1 0
## 631 born at Duke 0 1 0 0 0 vaginal 8 0 0 0 0
## 632 born at Duke 1 0 0 1 1 abdominal 7 0 0 1 0
## 633 born at Duke 1 0 0 1 1 abdominal NA NA NA NA NA
## 634 born at Duke 1 0 0 1 1 abdominal 8 1 1 1 1
## 635 born at Duke 1 16 0 1 1 abdominal 7 1 1 1 NA
## 636 born at Duke 0 18 0 0 1 abdominal 4 0 0 0 0
## 637 born at Duke 0 0 0 0 0 abdominal 5 1 1 1 1
## 638 born at Duke 0 2 1 0 0 vaginal 6 1 0 0 0
## 639 born at Duke 0 NA NA NA NA vaginal 8 NA NA NA NA
## 640 transported 0 NA NA NA NA vaginal 3 1 0 NA 1
## 641 transported 0 NA 0 NA NA vaginal 4 1 0 1 1
## 642 born at Duke 0 1 0 0 0 vaginal 9 0 0 0 0
## 643 born at Duke 0 1 0 0 0 vaginal 1 1 0 1 1
## 644 transported 0 NA 0 NA NA abdominal 5 1 0 1 1
## 645 born at Duke 0 0 1 0 0 abdominal 5 NA NA NA NA
## 646 born at Duke 0 3 0 0 0 vaginal 1 NA 0 0 NA
## 647 born at Duke 0 18 0 0 0 vaginal 4 1 0 0 1
## 648 born at Duke 0 0 0 0 0 abdominal 8 0 0 0 0
## 649 born at Duke 1 12 0 0 0 abdominal 6 0 0 0 0
## 650 born at Duke 1 12 0 0 0 abdominal 1 0 0 0 0
## 651 born at Duke 0 24 0 0 1 abdominal 4 1 0 1 1
## 652 born at Duke 0 8 0 1 0 vaginal 6 1 0 0 0
## 653 born at Duke 1 5 1 1 1 abdominal 7 1 1 0 NA
## 654 born at Duke 1 5 1 1 1 abdominal 6 1 1 1 NA
## 655 born at Duke 1 NA 1 1 0 abdominal 8 1 0 0 1
## 656 born at Duke 1 NA 1 1 0 abdominal 5 1 1 1 0
## 657 born at Duke 0 31 0 0 1 vaginal 3 1 0 0 NA
## 658 born at Duke 0 20 1 0 0 vaginal 1 NA 1 0 NA
## 659 transported 0 NA NA NA NA abdominal 2 1 1 1 1
## 660 born at Duke 1 11 0 0 0 abdominal 8 1 1 1 1
## 661 born at Duke 1 11 0 0 0 abdominal 8 1 1 0 0
## 662 transported 1 9 0 0 0 vaginal 5 0 0 0 0
## 663 transported 0 4 0 0 0 vaginal 3 1 0 1 1
## 664 transported 0 NA 0 0 0 vaginal 4 0 0 0 0
## 665 <NA> 0 0 NA NA NA abdominal NA NA NA NA NA
## 666 born at Duke 0 5 NA 1 1 vaginal 8 0 0 0 0
## 667 transported 0 22 0 0 0 vaginal 6 1 1 0 1
## 668 born at Duke 0 6 NA 0 0 vaginal 8 1 0 1 1
## 669 born at Duke 0 0 0 0 0 abdominal 5 1 0 1 1
## 670 born at Duke 1 0 0 0 0 abdominal 5 1 0 1 NA
## 671 born at Duke 0 6 0 0 0 vaginal 5 1 0 1 1
## pvh ivh ipe year sex dead
## 1 <NA> <NA> <NA> 81.51196 female 0
## 2 <NA> <NA> <NA> 81.51471 female 0
## 3 <NA> <NA> <NA> 81.55304 female 1
## 4 <NA> <NA> <NA> 81.55847 male 0
## 5 definite definite <NA> 81.59406 female 1
## 6 absent absent absent 81.60229 female 0
## 7 <NA> <NA> <NA> 81.61053 female 0
## 8 <NA> <NA> <NA> NA <NA> 1
## 9 absent absent absent NA <NA> 1
## 10 <NA> <NA> <NA> 81.62421 female 0
## 11 <NA> <NA> <NA> 81.62695 male 0
## 12 <NA> <NA> <NA> NA <NA> 1
## 13 absent absent absent 81.68445 male 0
## 14 absent absent absent 81.68988 male 0
## 15 <NA> <NA> <NA> 81.69537 female 1
## 16 absent absent absent 81.69812 male 0
## 17 possible absent absent 81.70636 male 0
## 18 <NA> <NA> <NA> 81.71179 female 0
## 19 definite absent absent 81.71179 male 0
## 20 definite definite absent 81.72003 male 0
## 21 absent absent absent 81.74738 female 0
## 22 absent absent absent 81.75836 female 0
## 23 absent absent absent 81.76386 female 0
## 24 absent absent absent NA <NA> 1
## 25 absent absent absent 81.77753 female 0
## 26 <NA> <NA> <NA> NA <NA> 1
## 27 possible absent absent 81.82678 female 1
## 28 absent absent absent 81.83502 female 0
## 29 <NA> <NA> <NA> 81.87335 female 0
## 30 definite absent absent 81.96368 female 0
## 31 absent absent absent 81.96643 female 0
## 32 absent absent absent 81.96643 female 0
## 33 <NA> <NA> <NA> NA <NA> 1
## 34 <NA> <NA> <NA> NA <NA> 1
## 35 absent absent absent 81.98010 male 0
## 36 possible absent absent 81.98834 male 0
## 37 <NA> <NA> <NA> NA <NA> 1
## 38 <NA> <NA> <NA> NA <NA> 1
## 39 possible absent absent 82.02734 male 0
## 40 absent absent absent 82.02734 female 0
## 41 possible absent absent 82.02734 female 0
## 42 absent absent absent 82.05475 male 0
## 43 definite absent absent 82.05743 female 0
## 44 <NA> <NA> <NA> NA <NA> 1
## 45 absent absent absent 82.08484 female 0
## 46 absent absent absent 82.10950 female 0
## 47 absent absent absent 82.10950 female 0
## 48 absent absent absent 82.13409 male 0
## 49 <NA> <NA> <NA> NA <NA> 1
## 50 absent absent absent 82.16425 female 0
## 51 <NA> <NA> <NA> 82.16425 male 0
## 52 definite definite definite 82.16974 male 1
## 53 absent absent absent 82.20532 male 0
## 54 absent absent absent 82.20807 female 0
## 55 absent absent absent 82.21075 female 0
## 56 absent absent absent 82.24091 male 0
## 57 <NA> <NA> <NA> 82.24908 female 1
## 58 absent absent absent 82.26825 female 0
## 59 <NA> <NA> <NA> 82.27100 female 0
## 60 definite absent absent 82.27100 female 0
## 61 absent absent absent 82.29840 male 1
## 62 definite absent absent 82.30115 female 0
## 63 <NA> <NA> <NA> NA <NA> 1
## 64 <NA> <NA> <NA> NA <NA> 1
## 65 absent absent absent 82.30115 male 1
## 66 absent absent absent 82.30115 male 0
## 67 absent absent absent 82.30115 female 1
## 68 possible absent absent 82.33124 female 0
## 69 definite absent absent 82.35040 male 1
## 70 absent absent absent 82.35040 male 0
## 71 absent absent absent NA <NA> 1
## 72 <NA> <NA> <NA> 82.35864 female 0
## 73 absent absent absent NA <NA> 1
## 74 absent absent absent 82.36682 male 0
## 75 <NA> <NA> <NA> 82.37231 male 0
## 76 absent absent absent 82.39148 female 0
## 77 absent absent absent 82.41888 female 0
## 78 absent absent absent 82.42157 male 0
## 79 absent absent absent 82.42157 female 0
## 80 <NA> <NA> <NA> 82.43530 male 0
## 81 definite definite absent 82.43805 female 0
## 82 definite absent absent 82.44623 female 0
## 83 <NA> <NA> <NA> 82.45990 male 0
## 84 absent absent absent 82.51471 male 0
## 85 absent absent absent 82.51196 female 0
## 86 <NA> <NA> <NA> 82.52563 female 0
## 87 definite absent absent 82.53656 male 0
## 88 possible absent absent 82.53656 female 0
## 89 absent absent absent NA <NA> 1
## 90 absent absent absent 82.56396 female 1
## 91 definite absent absent 82.57220 male 0
## 92 definite absent absent 82.58038 female 1
## 93 possible absent absent 82.59137 female 1
## 94 definite absent absent 82.58588 male 0
## 95 definite absent absent 82.59955 male 0
## 96 absent absent absent 82.59955 male 0
## 97 absent absent absent 82.60229 female 0
## 98 absent absent absent 82.60229 female 0
## 99 absent absent absent 82.61597 male 0
## 100 definite absent absent 82.63239 male 0
## 101 possible absent absent 82.63788 male 0
## 102 <NA> <NA> <NA> 82.67346 male 0
## 103 absent absent absent 82.67621 female 0
## 104 <NA> <NA> <NA> 82.68988 male 0
## 105 <NA> <NA> <NA> 82.68988 female 0
## 106 <NA> <NA> <NA> NA <NA> 1
## 107 <NA> <NA> <NA> 82.71179 female 0
## 108 <NA> <NA> <NA> 82.71454 male 0
## 109 absent absent absent 82.71729 male 0
## 110 definite absent absent 82.73920 female 0
## 111 definite absent absent 82.79669 male 0
## 112 <NA> <NA> <NA> 82.81860 male 1
## 113 absent absent absent NA <NA> 1
## 114 <NA> <NA> <NA> 82.83502 male 0
## 115 definite absent absent 82.87610 female 0
## 116 absent absent absent 82.87885 male 0
## 117 absent absent absent 82.88153 male 0
## 118 <NA> <NA> <NA> 82.88428 male 0
## 119 absent absent absent 82.88977 male 0
## 120 <NA> <NA> <NA> 82.88977 female 0
## 121 <NA> <NA> <NA> 82.89252 female 0
## 122 <NA> <NA> <NA> 82.89252 male 0
## 123 <NA> <NA> <NA> NA <NA> 1
## 124 absent absent absent 82.89526 female 0
## 125 definite absent absent 82.93903 male 0
## 126 absent absent absent 82.94177 male 0
## 127 absent absent absent 82.94452 male 1
## 128 <NA> <NA> <NA> 82.95276 female 0
## 129 <NA> <NA> <NA> 82.95551 male 0
## 130 definite definite absent 82.96094 female 1
## 131 absent absent absent 82.96643 male 0
## 132 absent absent absent 82.97467 male 0
## 133 absent absent absent 82.98285 female 0
## 134 absent absent absent 83.00000 female 0
## 135 <NA> <NA> <NA> 83.00543 male 1
## 136 absent absent absent 83.00543 male 1
## 137 definite definite absent 83.00818 female 0
## 138 <NA> <NA> <NA> 83.02734 female 1
## 139 <NA> <NA> <NA> 83.04102 male 0
## 140 definite definite absent 83.05475 male 1
## 141 absent absent absent 83.06842 female 1
## 142 <NA> <NA> <NA> 83.07117 female 0
## 143 absent absent absent 83.07391 male 0
## 144 absent absent absent 83.07391 female 0
## 145 absent absent absent 83.07935 male 0
## 146 absent absent absent 83.09576 male 1
## 147 <NA> <NA> <NA> 83.11224 male 0
## 148 <NA> <NA> <NA> 83.11768 female 1
## 149 <NA> <NA> <NA> 83.12866 female 0
## 150 absent absent absent 83.13409 female 1
## 151 absent absent absent 83.15875 male 0
## 152 absent absent absent 83.16699 female 0
## 153 definite definite absent 83.16699 female 1
## 154 <NA> <NA> <NA> 83.17517 female 0
## 155 <NA> <NA> <NA> 83.18890 male 0
## 156 <NA> <NA> <NA> 83.19708 male 0
## 157 absent absent absent 83.19708 male 1
## 158 <NA> <NA> <NA> 83.24091 female 0
## 159 <NA> <NA> <NA> 83.25183 male 0
## 160 <NA> <NA> <NA> 83.30389 female 0
## 161 absent absent absent 83.31207 male 1
## 162 possible absent absent 83.31757 male 0
## 163 <NA> <NA> <NA> 83.31757 male 0
## 164 absent absent absent 83.31757 male 0
## 165 <NA> <NA> <NA> 83.32849 female 0
## 166 possible absent absent 83.33948 male 0
## 167 definite definite absent 83.36682 male 1
## 168 absent absent absent 83.38324 male 0
## 169 absent absent absent 83.38324 male 0
## 170 absent absent absent 83.38324 female 0
## 171 possible absent absent 83.41064 male 1
## 172 absent absent absent 83.42157 female 0
## 173 absent definite absent 83.42432 male 0
## 174 <NA> <NA> <NA> 83.42981 female 0
## 175 definite absent definite 83.43256 female 1
## 176 absent absent definite 83.43805 male 0
## 177 definite definite absent 83.46814 female 0
## 178 absent absent absent 83.47906 male 1
## 179 definite definite absent 83.47906 female 1
## 180 definite absent absent 83.49005 female 0
## 181 absent absent absent 83.49823 male 1
## 182 absent absent absent 83.51739 male 1
## 183 absent absent absent 83.51739 male 0
## 184 <NA> <NA> <NA> 83.51739 female 0
## 185 absent absent absent 83.52563 female 0
## 186 definite absent absent 83.53931 female 0
## 187 <NA> <NA> <NA> 83.54480 female 0
## 188 possible absent absent 83.54755 male 0
## 189 absent absent absent 83.56122 male 0
## 190 <NA> <NA> <NA> 83.56122 female 0
## 191 absent absent absent 83.57489 male 0
## 192 absent definite absent 83.57489 female 1
## 193 absent possible absent 83.58038 female 0
## 194 definite definite absent 83.59406 female 1
## 195 definite absent absent 83.59137 female 1
## 196 absent absent absent 83.59680 female 0
## 197 <NA> <NA> <NA> 83.60229 male 0
## 198 absent absent absent 83.60504 male 0
## 199 absent absent absent 83.61597 female 0
## 200 absent absent absent 83.61871 female 1
## 201 <NA> <NA> <NA> 83.62695 female 0
## 202 absent absent absent 83.64062 male 1
## 203 absent absent absent 83.65704 female 0
## 204 absent absent absent 83.65704 female 1
## 205 <NA> <NA> <NA> 83.66254 male 0
## 206 definite definite definite 83.66803 male 0
## 207 <NA> <NA> <NA> 83.67621 female 0
## 208 <NA> <NA> <NA> 83.67621 male 0
## 209 <NA> <NA> <NA> 83.72552 male 1
## 210 <NA> <NA> <NA> 83.68170 female 0
## 211 absent absent absent 83.68170 female 0
## 212 <NA> <NA> <NA> 83.69263 female 0
## 213 absent absent absent 83.69537 female 0
## 214 definite definite absent 83.71729 male 1
## 215 absent absent absent 83.73370 male 0
## 216 <NA> <NA> <NA> 83.75562 male 0
## 217 absent absent absent 83.75562 female 0
## 218 absent absent absent 83.76386 female 0
## 219 <NA> <NA> <NA> 83.76929 female 0
## 220 absent absent absent 83.77753 male 0
## 221 definite definite absent 83.77753 female 1
## 222 <NA> <NA> <NA> 83.77753 female 0
## 223 absent absent absent 83.78845 female 0
## 224 absent absent absent 83.79395 female 1
## 225 absent absent absent 83.81036 male 0
## 226 absent absent absent 83.81586 female 0
## 227 <NA> <NA> <NA> 83.83228 male 0
## 228 absent absent absent 83.86237 male 0
## 229 <NA> <NA> <NA> 83.87335 male 0
## 230 <NA> <NA> <NA> 83.88428 female 0
## 231 <NA> <NA> <NA> 83.88428 female 0
## 232 absent absent absent 83.89801 male 0
## 233 absent absent absent 83.89801 male 0
## 234 possible absent absent 83.90344 female 1
## 235 absent absent absent 83.90894 male 1
## 236 absent absent absent 83.90894 female 0
## 237 absent absent absent 83.93359 female 0
## 238 absent absent absent 83.94177 female 0
## 239 absent absent absent 83.96918 male 1
## 240 absent absent absent 83.99384 female 0
## 241 absent absent absent 84.00269 male 0
## 242 absent absent absent 84.00269 female 0
## 243 absent absent absent 84.00818 female 0
## 244 <NA> <NA> absent 84.01367 male 0
## 245 absent absent absent 84.03009 female 0
## 246 absent absent absent 84.04376 female 0
## 247 <NA> <NA> <NA> 84.05200 female 1
## 248 absent absent absent 84.07391 male 0
## 249 absent definite absent 84.08759 male 0
## 250 <NA> <NA> <NA> 84.12042 female 0
## 251 <NA> <NA> <NA> 84.12592 female 0
## 252 absent absent absent NA male 0
## 253 absent possible absent 84.14508 male 0
## 254 <NA> absent absent 84.15601 male 0
## 255 absent absent absent 84.18890 female 0
## 256 <NA> <NA> <NA> 84.19159 male 0
## 257 absent absent absent 84.19983 male 0
## 258 definite definite absent 84.20258 male 1
## 259 absent absent absent 84.20532 female 0
## 260 <NA> <NA> <NA> 84.21350 female 0
## 261 absent absent absent 84.20807 male 1
## 262 <NA> <NA> <NA> 84.22174 male 0
## 263 absent absent absent 84.25183 female 0
## 264 <NA> <NA> <NA> 84.26007 male 0
## 265 absent definite absent 84.27649 female 0
## 266 absent absent absent 84.28473 male 1
## 267 absent absent absent 84.29016 male 0
## 268 absent absent absent 84.30115 female 0
## 269 absent absent absent 84.30115 male 0
## 270 absent absent absent 84.30389 male 1
## 271 absent absent absent 84.32031 male 0
## 272 absent absent absent 84.33124 female 0
## 273 absent absent absent 84.33948 female 0
## 274 absent absent absent 84.33948 female 0
## 275 absent absent absent 84.35040 female 0
## 276 absent absent absent 84.35315 female 0
## 277 absent absent absent 84.38055 male 0
## 278 absent absent absent 84.39148 female 0
## 279 absent absent absent 84.41339 female 1
## 280 absent absent absent 84.44348 male 0
## 281 absent absent absent 84.46539 male 0
## 282 absent absent absent 84.46539 female 0
## 283 absent absent absent 84.47638 male 1
## 284 absent absent absent 84.47906 male 0
## 285 absent absent absent 84.49280 female 0
## 286 <NA> <NA> <NA> 84.49823 male 0
## 287 <NA> <NA> <NA> 84.50372 male 1
## 288 absent absent absent 84.50647 female 0
## 289 absent absent absent 84.51196 male 0
## 290 absent absent absent 84.52014 female 0
## 291 definite definite absent 84.53656 female 1
## 292 absent absent absent 84.54205 female 0
## 293 definite definite absent 84.54480 female 0
## 294 <NA> <NA> <NA> 84.54755 male 0
## 295 absent absent absent 84.55029 female 0
## 296 absent absent absent 84.56122 male 0
## 297 absent absent absent 84.56396 male 0
## 298 absent absent absent 84.57220 male 0
## 299 <NA> <NA> <NA> 84.57489 female 0
## 300 <NA> <NA> <NA> 84.57489 female 0
## 301 possible definite absent 84.57764 male 1
## 302 <NA> <NA> <NA> 84.58313 male 0
## 303 absent absent absent 84.59955 male 0
## 304 absent absent absent 84.61053 male 0
## 305 absent definite definite 84.62421 male 1
## 306 <NA> <NA> <NA> 84.62421 female 0
## 307 <NA> <NA> <NA> 84.63239 female 0
## 308 definite definite absent 84.64062 male 1
## 309 <NA> <NA> <NA> 84.64062 female 0
## 310 <NA> <NA> <NA> 84.64337 male 0
## 311 <NA> <NA> <NA> 84.64612 male 0
## 312 <NA> <NA> <NA> 84.67072 male 1
## 313 definite definite definite 84.67896 male 1
## 314 absent absent absent 84.68170 female 0
## 315 absent absent absent 84.68445 male 0
## 316 absent absent absent 84.68719 female 0
## 317 absent absent absent 84.68988 male 0
## 318 absent absent absent 84.69537 male 0
## 319 absent absent absent 84.70905 female 0
## 320 <NA> <NA> <NA> 84.70905 male 0
## 321 absent absent absent 84.71729 male 0
## 322 absent absent absent 84.72552 female 0
## 323 definite absent absent 84.72278 male 1
## 324 definite definite absent 84.73920 male 1
## 325 absent absent absent 84.74194 male 0
## 326 absent absent absent 84.75012 male 0
## 327 absent absent absent 84.75012 female 0
## 328 absent absent absent 84.76111 female 0
## 329 <NA> <NA> <NA> 84.77203 female 0
## 330 <NA> <NA> <NA> 84.77478 male 0
## 331 absent absent absent 84.77753 female 0
## 332 absent absent absent 84.78302 female 0
## 333 possible absent absent 84.79669 female 0
## 334 <NA> <NA> <NA> 84.80487 female 0
## 335 absent definite absent 84.82678 female 1
## 336 <NA> <NA> <NA> 84.82953 male 0
## 337 absent absent absent 84.83228 female 0
## 338 absent definite absent 84.84320 female 1
## 339 <NA> <NA> <NA> 84.86237 male 1
## 340 absent absent absent 84.87335 female 0
## 341 absent definite absent 84.88153 female 1
## 342 absent absent absent 84.88702 male 0
## 343 definite absent absent 84.88977 male 0
## 344 <NA> <NA> <NA> 84.89526 female 0
## 345 absent absent absent 84.90619 female 0
## 346 <NA> <NA> <NA> 84.90619 female 0
## 347 <NA> <NA> <NA> 84.90894 male 0
## 348 definite absent absent 84.90894 male 1
## 349 <NA> <NA> <NA> 84.90894 female 1
## 350 absent absent absent 84.91168 female 0
## 351 <NA> <NA> <NA> 84.91168 female 0
## 352 definite absent absent 84.92261 male 1
## 353 absent absent absent 84.93085 male 1
## 354 definite definite absent 84.93359 female 1
## 355 absent absent absent 84.94177 female 0
## 356 absent absent absent 84.94452 female 0
## 357 absent absent absent 84.94452 male 0
## 358 definite absent absent 84.95551 male 0
## 359 <NA> <NA> <NA> 84.97192 female 0
## 360 absent absent absent 84.98010 female 0
## 361 <NA> <NA> <NA> 84.98560 female 0
## 362 absent absent absent 84.98834 female 0
## 363 absent definite absent 84.99109 female 1
## 364 absent absent possible 85.00000 female 0
## 365 <NA> <NA> <NA> 85.01642 female 0
## 366 <NA> <NA> <NA> 85.01642 female 0
## 367 <NA> <NA> <NA> 85.85144 male 0
## 368 absent absent absent 85.02460 male 0
## 369 definite absent absent 85.02734 female 0
## 370 absent definite definite 85.03009 male 0
## 371 <NA> <NA> <NA> 85.03558 male 0
## 372 definite absent absent 85.04102 male 0
## 373 definite absent absent 85.04376 male 0
## 374 definite absent absent 85.04651 male 0
## 375 absent absent absent 85.06842 male 0
## 376 <NA> <NA> <NA> 85.08759 male 0
## 377 possible definite definite 85.09576 female 0
## 378 <NA> <NA> <NA> 85.10126 male 0
## 379 definite absent absent 85.10400 male 0
## 380 absent absent absent 85.10675 female 0
## 381 absent absent absent 85.11768 female 0
## 382 absent absent absent 85.12042 male 0
## 383 absent absent absent 85.13684 female 1
## 384 absent absent absent 85.14233 female 0
## 385 absent absent absent 85.16974 male 0
## 386 definite absent absent 85.17242 female 0
## 387 absent absent absent 85.17517 female 0
## 388 definite absent absent 85.17517 male 0
## 389 absent absent absent 85.18066 female 0
## 390 possible absent absent 85.18616 female 0
## 391 absent absent absent 85.18890 female 1
## 392 definite absent absent 85.18890 female 1
## 393 definite absent absent 85.19434 male 1
## 394 absent absent absent 85.19434 male 0
## 395 absent absent absent 85.20258 male 0
## 396 absent absent absent 85.20258 male 0
## 397 definite definite definite 85.21350 male 1
## 398 absent absent absent 85.22449 male 0
## 399 definite definite absent 85.23541 female 1
## 400 definite definite definite 85.23816 male 1
## 401 absent absent absent 85.23816 female 0
## 402 <NA> <NA> <NA> 85.25183 male 0
## 403 absent definite absent 85.26007 male 1
## 404 absent definite possible 85.26007 female 1
## 405 definite possible absent 85.27374 male 0
## 406 absent absent absent 85.27374 female 0
## 407 absent absent absent 85.27374 male 0
## 408 possible absent absent 85.27374 female 0
## 409 <NA> <NA> <NA> 85.27649 male 0
## 410 absent absent absent 85.27649 female 0
## 411 definite absent absent 85.28741 female 0
## 412 definite definite absent 85.30115 male 1
## 413 <NA> <NA> <NA> 85.31482 female 0
## 414 definite definite absent 85.32849 female 0
## 415 definite possible absent 85.33673 male 0
## 416 <NA> <NA> <NA> 85.34222 female 0
## 417 absent absent possible 85.34491 male 0
## 418 absent definite definite 85.35864 male 1
## 419 absent absent absent 85.36957 female 0
## 420 absent absent absent 85.37781 female 0
## 421 absent absent absent 85.38055 female 0
## 422 absent absent absent 85.39148 male 0
## 423 <NA> <NA> <NA> 85.39423 male 0
## 424 definite absent possible 85.40240 male 0
## 425 absent absent possible 85.40515 male 0
## 426 absent definite absent 85.40790 male 0
## 427 absent absent absent 85.41064 female 0
## 428 definite absent absent 85.42432 female 0
## 429 definite absent absent 85.42432 female 0
## 430 <NA> <NA> <NA> 85.42706 female 0
## 431 absent absent absent 85.43805 female 0
## 432 definite absent absent 85.43805 male 1
## 433 absent absent absent 85.44073 male 0
## 434 absent absent possible 85.44623 male 0
## 435 absent absent definite 85.45447 male 0
## 436 possible absent absent 85.45990 male 0
## 437 absent absent absent 85.46539 female 0
## 438 absent absent absent 85.46814 female 0
## 439 absent definite absent 85.47363 male 0
## 440 absent possible definite 85.47906 male 1
## 441 absent absent absent 85.49280 female 0
## 442 possible absent absent 85.50922 female 0
## 443 possible absent absent 85.53113 female 0
## 444 definite absent definite 85.52563 female 0
## 445 absent absent absent 85.53113 male 0
## 446 definite absent absent 85.53931 male 0
## 447 absent definite definite 85.54755 female 0
## 448 absent definite definite 85.56671 female 1
## 449 absent absent possible 85.56946 male 0
## 450 absent absent absent 85.58588 male 0
## 451 definite possible absent 85.59406 female 0
## 452 definite absent absent 85.59680 male 1
## 453 absent absent absent 85.60504 female 0
## 454 definite definite absent 85.61597 female 1
## 455 definite absent absent 85.61871 male 0
## 456 <NA> <NA> <NA> 85.62421 male 0
## 457 definite absent absent 85.63788 male 0
## 458 possible absent definite 85.63788 female 0
## 459 absent absent absent 85.65979 male 0
## 460 absent absent definite 85.66803 male 0
## 461 definite absent absent 85.67346 male 0
## 462 absent definite absent 85.67621 male 0
## 463 absent absent absent 85.68719 male 0
## 464 absent absent absent 85.68719 female 0
## 465 absent absent absent 85.68719 female 0
## 466 absent absent absent 85.68719 male 0
## 467 <NA> <NA> <NA> 85.68988 female 0
## 468 definite absent absent 85.72552 male 0
## 469 absent definite definite 85.73645 male 0
## 470 definite definite absent 85.75287 male 0
## 471 absent absent absent 85.76111 male 0
## 472 absent absent absent 85.77203 male 0
## 473 absent absent absent 85.77203 male 0
## 474 definite absent absent 85.77753 female 0
## 475 definite absent absent 85.78027 male 0
## 476 definite absent absent 85.78571 male 0
## 477 <NA> <NA> <NA> 85.79120 male 0
## 478 absent definite absent 85.79395 male 0
## 479 absent absent absent 85.79669 male 0
## 480 absent definite absent 85.80487 female 0
## 481 absent absent absent 85.82404 male 0
## 482 absent absent absent NA female 0
## 483 definite definite definite 85.87335 male 1
## 484 absent definite possible 86.88428 male 0
## 485 absent definite absent 85.88702 male 0
## 486 absent definite definite 85.89801 male 0
## 487 absent definite absent 86.89801 female 1
## 488 definite absent absent 85.91168 male 0
## 489 <NA> <NA> <NA> 85.91443 male 1
## 490 definite absent absent 85.91718 female 0
## 491 absent absent absent 85.92535 male 0
## 492 possible absent absent 85.94452 female 0
## 493 absent absent absent 85.95551 male 0
## 494 definite absent absent 85.97192 female 0
## 495 definite absent absent 85.97467 male 0
## 496 absent absent absent 85.97467 male 1
## 497 absent absent absent 85.99109 female 0
## 498 absent absent absent 85.99109 female 0
## 499 <NA> <NA> <NA> 86.00000 male 1
## 500 definite absent absent 86.00000 female 0
## 501 definite absent absent 86.00818 male 0
## 502 definite absent absent 86.00818 male 0
## 503 absent absent absent 86.01093 male 0
## 504 definite absent definite 86.01910 male 0
## 505 absent absent absent 86.02185 female 0
## 506 <NA> <NA> <NA> 86.02185 male 1
## 507 possible absent absent 86.03827 male 0
## 508 absent definite definite 86.04926 male 0
## 509 absent definite possible 86.05475 male 0
## 510 absent absent absent 86.07117 female 0
## 511 absent absent absent 86.07391 male 0
## 512 definite absent possible 86.08484 male 0
## 513 absent absent absent 86.09308 male 0
## 514 <NA> <NA> <NA> 86.09576 male 0
## 515 possible absent possible 86.10126 female 0
## 516 <NA> <NA> <NA> 86.10675 male 0
## 517 definite absent absent 86.10675 male 0
## 518 absent definite definite 86.13684 male 1
## 519 possible absent possible 86.14233 female 0
## 520 absent absent absent 86.18616 male 0
## 521 absent absent absent 86.16425 female 0
## 522 absent absent absent 86.16699 female 0
## 523 absent absent definite 86.16699 female 0
## 524 definite definite absent 86.18066 male 0
## 525 definite absent absent 86.19159 female 0
## 526 absent absent absent 86.19159 male 0
## 527 definite definite absent 86.20807 female 0
## 528 definite absent absent 86.22723 male 0
## 529 absent absent absent 86.16699 male 0
## 530 possible absent absent 86.24365 female 0
## 531 possible absent absent 86.24640 female 0
## 532 absent absent absent 86.25458 female 0
## 533 absent absent absent 86.25732 female 0
## 534 absent absent absent 86.26825 female 0
## 535 definite absent absent 86.26825 male 0
## 536 absent absent absent 86.26825 male 0
## 537 possible absent absent 86.26825 male 0
## 538 absent absent absent 86.27924 male 0
## 539 absent absent absent 86.28741 female 0
## 540 absent absent absent 86.29291 female 0
## 541 absent absent absent 86.29840 male 1
## 542 definite definite absent 86.33673 female 0
## 543 absent absent absent 86.33948 female 0
## 544 absent absent absent 86.34222 female 1
## 545 absent absent absent 86.34222 female 0
## 546 absent absent absent 86.34766 female 0
## 547 <NA> <NA> <NA> 86.35590 female 1
## 548 absent absent absent 86.36957 male 1
## 549 possible absent absent 86.38055 male 0
## 550 absent absent absent 86.38324 male 0
## 551 absent absent absent 86.38324 female 0
## 552 absent absent absent 86.40240 female 0
## 553 absent definite absent 86.40790 female 1
## 554 absent absent absent 86.42157 male 0
## 555 absent absent absent 86.42157 male 0
## 556 definite absent absent 86.42706 male 0
## 557 <NA> <NA> <NA> 86.43256 male 0
## 558 definite absent absent 86.43530 male 0
## 559 <NA> <NA> <NA> 86.44623 male 1
## 560 absent absent absent 86.45447 male 0
## 561 absent absent absent 86.45721 male 0
## 562 absent absent absent 86.45990 female 0
## 563 absent absent absent 86.46539 male 0
## 564 definite possible absent 86.47089 male 0
## 565 absent absent absent 86.47363 female 0
## 566 possible absent possible 86.47638 female 1
## 567 absent definite definite 86.52563 female 1
## 568 definite absent absent 86.53931 male 0
## 569 absent absent absent 86.55573 male 0
## 570 <NA> <NA> <NA> 86.55573 male 1
## 571 absent absent absent 86.56122 female 0
## 572 absent absent definite 86.56122 female 0
## 573 absent absent absent 86.56396 male 0
## 574 absent possible absent 86.57764 male 1
## 575 absent absent absent 86.58038 male 0
## 576 absent absent absent 86.58862 male 0
## 577 absent absent definite 86.60229 female 0
## 578 definite absent absent 86.61053 female 0
## 579 absent absent absent 86.63788 female 0
## 580 definite absent absent 86.63788 female 0
## 581 absent absent definite 86.64062 female 0
## 582 absent absent absent 86.64612 female 1
## 583 definite absent possible 86.65155 female 0
## 584 definite absent absent 86.66528 female 0
## 585 absent absent absent 86.69263 male 0
## 586 definite absent definite 86.69812 female 0
## 587 absent absent possible 86.70636 female 0
## 588 absent absent absent 86.70905 male 0
## 589 possible absent absent 86.71454 <NA> 0
## 590 definite absent absent 86.73096 female 0
## 591 absent absent absent 86.73920 female 0
## 592 absent absent absent 86.75012 female 0
## 593 absent absent absent 86.75287 female 0
## 594 absent definite absent 86.76111 female 0
## 595 absent absent absent 86.76929 female 0
## 596 <NA> <NA> <NA> 86.77478 female 1
## 597 absent absent absent 86.81036 male 0
## 598 absent absent absent 86.82953 female 1
## 599 definite absent absent 86.84320 male 0
## 600 possible absent definite 86.87610 female 1
## 601 definite absent definite 86.87610 male 0
## 602 definite absent possible 86.87885 male 0
## 603 <NA> <NA> <NA> 86.88977 female 0
## 604 absent absent absent 86.89526 male 0
## 605 absent absent absent 86.89801 female 0
## 606 possible absent absent 86.90344 male 0
## 607 absent absent absent 86.92535 male 1
## 608 possible absent absent 86.93085 male 0
## 609 absent absent absent 86.94727 female 0
## 610 absent absent absent 86.94727 female 0
## 611 absent absent absent 86.95001 male 0
## 612 absent possible absent 86.96094 male 1
## 613 absent absent absent 86.98560 male 0
## 614 <NA> <NA> <NA> 86.99384 male 1
## 615 absent definite absent 86.99652 male 0
## 616 absent absent absent 87.00000 female 0
## 617 absent absent absent 87.01093 male 0
## 618 absent absent absent 87.02185 female 0
## 619 possible absent absent 87.02734 male 1
## 620 absent absent absent 87.03284 female 0
## 621 <NA> <NA> <NA> 87.01910 male 0
## 622 definite absent absent 87.06018 female 0
## 623 absent absent absent 87.07391 female 0
## 624 absent absent absent 87.07660 male 0
## 625 possible absent absent 87.07660 female 0
## 626 absent absent possible 87.07660 male 0
## 627 definite definite absent 87.08484 female 1
## 628 absent absent absent 87.08759 female 0
## 629 absent absent absent 87.08759 female 0
## 630 absent absent absent 87.09033 female 0
## 631 absent absent absent 87.11768 female 0
## 632 possible absent absent 87.12042 female 0
## 633 absent absent absent 87.12042 male 0
## 634 absent absent absent 87.12042 male 0
## 635 definite absent absent 87.12042 male 1
## 636 definite absent absent 87.14508 male 0
## 637 definite definite absent 87.16150 female 0
## 638 definite absent absent 87.19159 female 0
## 639 absent absent absent 87.21899 female 0
## 640 absent absent absent 87.21899 male 0
## 641 definite definite definite 87.22174 female 0
## 642 absent absent absent 87.22723 male 0
## 643 absent absent absent 87.23816 male 0
## 644 definite definite definite 87.24091 female 0
## 645 <NA> <NA> <NA> 87.24640 female 1
## 646 <NA> <NA> <NA> 87.27100 male 1
## 647 absent absent absent 87.27924 female 0
## 648 absent absent absent 87.28741 female 0
## 649 absent absent absent 87.30658 male 0
## 650 possible absent absent 87.30658 female 0
## 651 absent definite absent 87.31207 male 0
## 652 absent absent absent 87.32306 male 0
## 653 <NA> <NA> <NA> 87.32849 male 1
## 654 definite absent definite 87.32849 male 1
## 655 absent absent definite 87.32849 female 0
## 656 absent absent absent 87.32849 male 1
## 657 absent definite definite 87.33673 female 1
## 658 <NA> <NA> <NA> 87.33673 male 1
## 659 possible absent absent 87.35590 male 1
## 660 absent absent absent 87.36139 female 0
## 661 definite definite absent 87.36139 female 0
## 662 <NA> <NA> <NA> 87.40515 male 0
## 663 definite absent absent 87.41614 male 0
## 664 definite definite definite 87.43530 female 0
## 665 absent absent absent 87.43805 <NA> 0
## 666 absent absent absent 87.45721 male 0
## 667 definite possible absent 87.46814 male 0
## 668 absent absent absent 87.47089 male 0
## 669 absent absent absent 87.47363 female 0
## 670 absent absent absent 87.47363 female 1
## 671 absent absent absent 87.48456 male 0cleaned_data<-original_data %>%
select_if(~ sum(is.na(.)) < 100) %>% #удаляем колонки с количеством пропусков больше 100
drop_na() #удаляем строки с NAПлотности распределения числовых данных
- Постройте графики плотности распределения для числовых переменных. Удалите выбросы, если таковые имеются. Преобразуйте категориальные переменные в факторы. Для любых двух числовых переменных раскрасьте график по переменной ‘inout’.
cleaned_data<-cleaned_data %>%
mutate(race=as.factor(race),
inout=as.factor(inout),
twn=as.factor(twn),
delivery=as.factor(delivery),
sex=as.factor(sex),
dead=as.factor(dead),
vent=as.factor(vent),
pneumo=as.factor(pneumo),
pda=as.factor(pda),
cld=as.factor(cld))
cleaned_data_num<-cleaned_data %>%
select_if(is.numeric) %>%
gather(key="variable", value="value")
density_plots<-ggplot(cleaned_data_num, aes(value)) +
geom_density() +
facet_wrap(~variable, scales="free")+
theme_classic()
bwt_plot<-ggplot(cleaned_data, aes(bwt, fill=inout)) +
geom_density(alpha = .5)+
theme_classic()
lowph_plot<-ggplot(cleaned_data, aes(lowph, fill=inout)) +
geom_density(alpha = .5)+
theme_classic()
density_plots
bwt_plot
lowph_plot
Удаляем выбросы благодаря боксплоту
cleaned_data_outliers<-cleaned_data %>%
mutate_if(is.numeric, ~replace(., . %in% boxplot.stats(.)$out,NA)) %>%
drop_na
cleaned_data_outliers_num<-cleaned_data_outliers %>%
select_if(is.numeric) %>%
gather(key="variable", value="value")
density_plots_out<-ggplot(cleaned_data_outliers_num, aes(value)) +
geom_density() +
facet_wrap(~variable, scales="free")+
theme_classic()
density_plots_out
# Сравнение числовой переменной по группам 3. Проведите тест на
сравнение значений колонки ‘lowph’ между группами в переменной inout.
Вид статистического теста определите самостоятельно. Визуализируйте
результат через библиотеку ‘rstatix’. Как бы вы интерпретировали
результат, если бы знали, что более низкое значение lowph ассоциировано
с более низкой выживаемостью?
stats<-cleaned_data_outliers %>%
select(lowph, inout) %>%
group_by(inout) %>%
get_summary_stats(lowph, type = "mean_ci")
IN<-c(stats$inout[1], stats$inout[2])
M<-c(stats$mean[1], stats$mean[2])
CI<-c(stats$ci[1], stats$ci[2])
tib<-tibble(IN,M, CI) %>% mutate(M=as.numeric(M),
CI=as.numeric(CI))
ggplot(tib,
aes(x = IN,
y = M)) +
geom_point()+
geom_errorbar(aes(ymin=M-CI,
ymax=M+CI))+
ylim(7.1,7.3)+
theme_minimal()
cleaned_data_outliers %>%
t_test(lowph ~ inout)%>%
add_significance()## Warning: The statistic is based on a difference or ratio; by default, for
## difference-based statistics, the explanatory variable is subtracted in the
## order "born at Duke" - "transported", or divided in the order "born at Duke" /
## "transported" for ratio-based statistics. To specify this order yourself,
## supply `order = c("born at Duke", "transported")`.## # A tibble: 1 × 7
## statistic t_df p_value alternative estimate lower_ci upper_ci
## <dbl> <dbl> <dbl> <chr> <dbl> <dbl> <dbl>
## 1 5.36 97.3 0.000000560 two.sided 0.0835 0.0526 0.114Вывод: Тест Стьюдента показал статистически значимое отличие в средних (с ош. первого рода = 0,05) между группами. 95% ДИ-лы не пересекаются. В группе transported более низкое значение lowph, и, принимая во внимание взаимосвязь с выживаемостью, по всей видимости, будет более низкая выживаемость.
Корреляционный анализ
- Сделайте новый датафрейм, в котором оставьте только континуальные или ранговые данные, кроме ‘birth’, ‘year’ и ‘exit’. Сделайте корреляционный анализ этих данных. Постройте два любых типа графиков для визуализации корреляций.
cleaned_data_outliers_contin <-cleaned_data_outliers %>%
select_if(is.numeric) %>%
select(-c('birth', 'year', 'exit') )
cleaned_data_outliers_contin_cor <- cor(cleaned_data_outliers_contin, method = "spearman")
corrplot(cleaned_data_outliers_contin_cor, method = 'number')
cleaned_data_outliers_contin_cor %>% network_plot(min_cor = .0)
Визуализируем самые сильные корреляции между данными:
gest - bwt
bwt - hospstay
gest - hospstay
gest_bwt<-cleaned_data_outliers_contin %>%
ggplot(aes(x = gest, y = bwt)) +
geom_point(size = 1.1) +
geom_smooth(method = "lm") +
theme_bw()
bwt_hospstay<-cleaned_data_outliers_contin %>%
ggplot(aes(x = bwt, y = hospstay)) +
geom_point(size = 1.1) +
geom_smooth(method = "lm") +
theme_bw()
gest_hospstay<-cleaned_data_outliers_contin %>%
ggplot(aes(x = gest, y = hospstay)) +
geom_point(size = 1.1) +
geom_smooth(method = "lm") +
theme_bw()
ct_gest_bwt<-cor.test(cleaned_data_outliers_contin$gest,
cleaned_data_outliers_contin$bwt, method = "spearman")## Warning in cor.test.default(cleaned_data_outliers_contin$gest,
## cleaned_data_outliers_contin$bwt, : Есть совпадающие значения: не могу
## высчитать точное p-значениеct_bwt_hospstay<-cor.test(cleaned_data_outliers_contin$bwt,
cleaned_data_outliers_contin$hospstay, method = "spearman")## Warning in cor.test.default(cleaned_data_outliers_contin$bwt,
## cleaned_data_outliers_contin$hospstay, : Есть совпадающие значения: не могу
## высчитать точное p-значениеct_gest_hospstay<-cor.test(cleaned_data_outliers_contin$gest,
cleaned_data_outliers_contin$hospstay, method = "spearman")## Warning in cor.test.default(cleaned_data_outliers_contin$gest,
## cleaned_data_outliers_contin$hospstay, : Есть совпадающие значения: не могу
## высчитать точное p-значениеct_gest_bwt##
## Spearman's rank correlation rho
##
## data: cleaned_data_outliers_contin$gest and cleaned_data_outliers_contin$bwt
## S = 6090452, p-value < 2.2e-16
## alternative hypothesis: true rho is not equal to 0
## sample estimates:
## rho
## 0.6855561gest_bwt## `geom_smooth()` using formula = 'y ~ x'
ct_bwt_hospstay##
## Spearman's rank correlation rho
##
## data: cleaned_data_outliers_contin$bwt and cleaned_data_outliers_contin$hospstay
## S = 28630816, p-value < 2.2e-16
## alternative hypothesis: true rho is not equal to 0
## sample estimates:
## rho
## -0.47818bwt_hospstay## `geom_smooth()` using formula = 'y ~ x'
ct_gest_hospstay##
## Spearman's rank correlation rho
##
## data: cleaned_data_outliers_contin$gest and cleaned_data_outliers_contin$hospstay
## S = 27413581, p-value < 2.2e-16
## alternative hypothesis: true rho is not equal to 0
## sample estimates:
## rho
## -0.4153354gest_hospstay## `geom_smooth()` using formula = 'y ~ x'
Корреляции действительно статистически значимые, однако корреляция между
gest и bwt оказалась самой сильной. Остальные показывают отрицательную
взаимосвязь.
Иерархическая кластеризация
- Постройте иерархическую кластеризацию на этом датафрейме. На основе дендрограммы предполагаю 3 кластера “высшего” уровня
#Стандартизуем данные
cleaned_data_outliers_contin_scaled <- scale(cleaned_data_outliers_contin)
#Матрица дистанций
data_dist <- dist(cleaned_data_outliers_contin_scaled,
method = "euclidean")
#Дендрограмма кластеров
data_dist.hc <- hclust(d = data_dist,
method = "ward.D2")
#Визуализируем
tree<-fviz_dend(data_dist.hc,
k=3,
cex = 0.6,
horiz = TRUE,
k_colors = "jco",
rect = TRUE,
rect_border = "jco",
rect_fill = TRUE) ## Warning: The `<scale>` argument of `guides()` cannot be `FALSE`. Use "none" instead as
## of ggplot2 3.3.4.
## ℹ The deprecated feature was likely used in the factoextra package.
## Please report the issue at <https://github.com/kassambara/factoextra/issues>.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.tree
6. Сделайте одновременный график heatmap и иерархической кластеризации.
Интерпретируйте результат.
Здесь видно, что bwt и gest расположены ближе всего друг к другу (корреляционный анализ показал нам бОльшую корреляцию). Разделение данных на 6 кластеров (по рядам), видимо, оптимально (хотя по некоторым колонкам все равно собираются в кластер и “синие” и “красные” значения). Вид данных схож у двух соседних веток. Переменная hospstay сильно отличается от других.
heat_tree<-pheatmap(cleaned_data_outliers_contin_scaled,
show_rownames = FALSE,
clustering_distance_rows = data_dist,
clustering_method = "ward.D2",
cutree_rows = 6,
cutree_cols = length(colnames(cleaned_data_outliers_contin_scaled)),
angle_col = 45,
main = "Dendrograms for clustering rows and columns with heatmap")
heat_tree
PCA анализ
- Проведите PCA анализ на этих данных. Проинтерпретируйте результат. Нужно ли применять шкалирование для этих данных перед проведением PCA?
Шкалирование перед PCA нужно (если не сделали его заранее). 90% дисперсии объясняют первые 5 компонент, а первые 2 компоненты объясняют 60% дисперсии. Это хороший результат разложения на главные компоненты.
cleaned_data_outliers_contin.pca <- prcomp(cleaned_data_outliers_contin,
scale = T)
summary(cleaned_data_outliers_contin.pca)## Importance of components:
## PC1 PC2 PC3 PC4 PC5 PC6
## Standard deviation 1.5954 1.0661 0.8823 0.8512 0.73334 0.52677
## Proportion of Variance 0.4242 0.1894 0.1298 0.1208 0.08963 0.04625
## Cumulative Proportion 0.4242 0.6136 0.7434 0.8641 0.95375 1.00000fviz_eig(cleaned_data_outliers_contin.pca, addlabels = T, ylim = c(0, 50))
fviz_pca_var(cleaned_data_outliers_contin.pca, col.var = "contrib")
fviz_pca_var(cleaned_data_outliers_contin.pca,
select.var = list(contrib = 3), # Задаём число здесь
col.var = "contrib")
Как и ожидалось, переменные bwt и gest схожи. Их контрибуция в первую главную компоненту высока. Аналогично, коррелируют данные lowp и apg1. Наблюдается отрицательная корреляция между hospstay и gest. Между переменными gest и pltct взаимосвязи нет (как и между apg1 и hospstay). 3 самые важные по контрибуции переменные: gest, bwt, pltct
Анализ наблюдений по PCA
- Постройте biplot график для PCA. Раскрасьте его по значению колонки ‘dead’.
cleaned_data_outliers_contin_death<-cleaned_data_outliers_contin %>%
bind_cols(cleaned_data_outliers$dead)## New names:
## • `` -> `...7`cleaned_data_outliers_contin_death<-cleaned_data_outliers_contin_death %>%
mutate (death=cleaned_data_outliers_contin_death$...7) %>%
select(-7)
#cleaned_data_outliers_contin_death<- cleaned_data_outliers_contin_death %>% mutate(death=as.numeric(death))
# Визуализируем с группировкой по death (для этого переменную нужно сделать фактором)
ggbiplot(cleaned_data_outliers_contin.pca,
scale=0,
groups = as.factor(cleaned_data_outliers_contin_death$death),
ellipse = T,
alpha = 0.2) +
theme_minimal()
- Переведите последний график в ‘plotly’. При наведении на точку нужно, чтобы отображалось id пациента.
#Введем id
cleaned_data_outliers_contin_id<-cleaned_data_outliers_contin %>%
mutate(id=row_number())
cleaned_data_outliers_contin_id.pca<-prcomp(cleaned_data_outliers_contin_id,
scale = T)
cleaned_data_outliers_contin_id.pca## Standard deviations (1, .., p=7):
## [1] 1.5961186 1.0713941 1.0130143 0.8770944 0.8397734 0.7265897 0.5252386
##
## Rotation (n x k) = (7 x 7):
## PC1 PC2 PC3 PC4 PC5 PC6
## hospstay 0.40956848 -0.2905703 -0.090450661 -0.3806966 0.50921760 -0.5649456
## lowph -0.38408753 -0.1820875 -0.335096185 0.2515291 0.70160554 0.3632872
## pltct -0.24776024 -0.6845516 -0.147636277 0.4148350 -0.29104628 -0.3903492
## bwt -0.52771199 0.1542432 0.205897898 -0.0538172 -0.08118278 -0.3709414
## gest -0.48672984 0.3450096 0.116189690 -0.1532577 0.25020211 -0.3648235
## apg1 -0.32619658 -0.4302458 -0.005077233 -0.7551238 -0.17732221 0.3218643
## id -0.03943611 0.2930326 -0.895440108 -0.1520490 -0.25120560 -0.1489834
## PC7
## hospstay 0.12745697
## lowph 0.13977352
## pltct -0.19758262
## bwt 0.71291702
## gest -0.64138696
## apg1 -0.05662837
## id 0.04842010pcadf <- data.frame(cleaned_data_outliers_contin_id.pca$x)
#Рисуем график 'plotly' распределения данных по 3 компонентам. (не смогла построить "стрелочки")
plly<- plot_ly(data = pcadf,
x=~PC1,
y=~PC2,
z=~PC3,
size = 1,
type="scatter3d",
mode="markers",
text=row_number(pcadf))
pllyИнтерпретация данных
- Дайте содержательную интерпретацию PCA анализу. Почему использовать колонку ‘dead’ для выводов об ассоциации с выживаемостью некорректно?
PCA анализ показывает, какие переменные вносят бОльший вклад в разделение данных по группам dead. Здесь группы по dead слабо соотноятся с bwt, gest и hospstay (слабо соотносятся с переменными с наибольшей контрибуцией в главные компоненты в том числе) . Лучше всего разделение по dead соотносится с lowph (однако, нам изначально известно, что lowph соотносится с выживаемостью): низкий lowph соотносится с меньшей выживаемостью (большей смертностью - синий эллипс)
#UMAP 11. Приведите ваши данные к размерности в две колонки через UMAP. Сравните результаты отображения точек между алгоритмами PCA и UMAP.
Не могу сделать UMAP из-за ошибки: Error in step_umap():
Caused by error in irlba::irlba(): ! функция
‘sexp_as_cholmod_sparse’ не предусмотрена в пакете ‘Matrix’ Backtrace:
1. … %>% juice() 14. uwot::umap(…) 15. uwot:::uwot(…) 16.
uwot:::spectral_init(V, ndim = n_components, verbose = verbose) 17.
uwot:::irlba_tsvd_normalized_laplacian_init(A, ndim, verbose = FALSE)
18. uwot:::irlba_spectral_tsvd(L, ndim + 1) 21. irlba::irlba(L, nv = n,
nu = 0, maxit = iters)